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    <title>LMArena - 开源AI模型评估平台</title>
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    <!-- Hero Section -->
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            <div class="text-center">
                <h1 class="text-5xl md:text-7xl font-bold mb-6 serif-font">LMArena</h1>
                <p class="text-xl md:text-2xl mb-8 opacity-90">开源AI模型评估平台</p>
                <p class="text-lg max-w-3xl mx-auto leading-relaxed opacity-80">
                    通过人类偏好评估大型语言模型，让每一次选择都基于真实的用户体验
                </p>
                <div class="mt-10 flex justify-center space-x-6">
                    <a href="https://lmarena.ai/" target="_blank" class="bg-white text-purple-700 px-8 py-3 rounded-full font-semibold hover:bg-gray-100 transition">
                        <i class="fas fa-external-link-alt mr-2"></i>访问平台
                    </a>
                    <a href="#features" class="border-2 border-white px-8 py-3 rounded-full font-semibold hover:bg-white hover:text-purple-700 transition">
                        了解更多
                    </a>
                </div>
            </div>
        </div>
    </section>

    <!-- Introduction Section -->
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        <div class="max-w-4xl mx-auto">
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                <h2 class="text-3xl font-bold mb-6 serif-font">为什么选择 LMArena？</h2>
                <div class="prose prose-lg max-w-none">
                    <p class="drop-cap text-gray-700 leading-relaxed">
                        在AI模型快速迭代的今天，选择合适的大语言模型变得越来越困难。传统的静态基准测试容易被"作弊"优化，主观评估又成本高昂且存在偏差。LMArena通过众包匿名战斗和Elo评分系统，为您提供动态、基于真实人类判断的模型排行榜。
                    </p>
                    <div class="mt-8 grid grid-cols-1 md:grid-cols-3 gap-6">
                        <div class="text-center">
                            <div class="text-4xl mb-3 feature-icon">
                                <i class="fas fa-users"></i>
                            </div>
                            <h3 class="font-semibold text-lg">社区驱动</h3>
                            <p class="text-gray-600 text-sm mt-2">数百万真实用户投票</p>
                        </div>
                        <div class="text-center">
                            <div class="text-4xl mb-3 feature-icon">
                                <i class="fas fa-chart-line"></i>
                            </div>
                            <h3 class="font-semibold text-lg">实时更新</h3>
                            <p class="text-gray-600 text-sm mt-2">动态排行榜持续演进</p>
                        </div>
                        <div class="text-center">
                            <div class="text-4xl mb-3 feature-icon">
                                <i class="fas fa-code-branch"></i>
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                            <h3 class="font-semibold text-lg">完全开源</h3>
                            <p class="text-gray-600 text-sm mt-2">透明可验证的评估方法</p>
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </section>

    <!-- Core Features Section -->
    <section id="features" class="py-16 px-6 bg-gray-100">
        <div class="max-w-6xl mx-auto">
            <h2 class="text-4xl font-bold text-center mb-12 serif-font">核心功能</h2>
            <div class="grid grid-cols-1 md:grid-cols-2 gap-8">
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                            <h3 class="text-xl font-bold mb-3">匿名模型战斗</h3>
                            <p class="text-gray-700 leading-relaxed">
                                用户输入提示后，随机收到两个模型的响应进行盲选投票。这种设计确保了公平比较，消除了品牌偏见，让评估更加客观和实用。
                            </p>
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                    </div>
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                            <h3 class="text-xl font-bold mb-3">多模态竞技场</h3>
                            <p class="text-gray-700 leading-relaxed">
                                支持文本、图像生成、视觉理解等不同领域。从聊天到多媒体生成，全面覆盖各种AI应用场景，满足不同需求。
                            </p>
                        </div>
                    </div>
                </div>
                <div class="bg-white rounded-xl p-8 card-hover">
                    <div class="flex items-start">
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                            <i class="fas fa-trophy"></i>
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                            <h3 class="text-xl font-bold mb-3">实时Elo排行榜</h3>
                            <p class="text-gray-700 leading-relaxed">
                                基于投票计算模型分数，持续更新。支持置信区间显示，帮助用户快速识别顶级模型及其可靠性。
                            </p>
                        </div>
                    </div>
                </div>
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                            <i class="fas fa-database"></i>
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                            <h3 class="text-xl font-bold mb-3">开源数据集共享</h3>
                            <p class="text-gray-700 leading-relaxed">
                                收集并公开人类偏好数据，包括数百万投票记录。便于研究者复现和扩展评估，促进AI社区协作。
                            </p>
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        </div>
    </section>

    <!-- Visualization Section -->
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            <h2 class="text-4xl font-bold text-center mb-12 serif-font">工作流程</h2>
            <div class="bg-white rounded-2xl shadow-xl p-10">
                <div class="mermaid">
                    graph LR
                        A[用户输入提示] --> B[系统随机分配模型]
                        B --> C[模型A生成响应]
                        B --> D[模型B生成响应]
                        C --> E[匿名展示结果]
                        D --> E
                        E --> F[用户投票选择]
                        F --> G[更新Elo评分]
                        G --> H[实时排行榜]
                        H --> I[数据集开源]
                        
                        style A fill:#f9f,stroke:#333,stroke-width:2px
                        style H fill:#9f9,stroke:#333,stroke-width:2px
                        style I fill:#99f,stroke:#333,stroke-width:2px
                </div>
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    </section>

    <!-- Use Cases Section -->
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            <h2 class="text-4xl font-bold text-center mb-12 serif-font">应用场景</h2>
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                    <h3 class="text-xl font-bold mb-3">开发者选型</h3>
                    <p class="text-gray-700">
                        在构建聊天机器人时，比较不同模型的响应质量，选择最适合的模型集成到应用中。
                    </p>
                </div>
                <div class="bg-white rounded-xl p-8 text-center card-hover">
                    <div class="text-5xl mb-4 text-purple-600">
                        <i class="fas fa-flask"></i>
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                    <h3 class="text-xl font-bold mb-3">研究评估</h3>
                    <p class="text-gray-700">
                        研究人员可以收集人类偏好数据，形成数据集用于学术分析和模型改进。
                    </p>
                </div>
                <div class="bg-white rounded-xl p-8 text-center card-hover">
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                        <i class="fas fa-briefcase"></i>
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                    <h3 class="text-xl font-bold mb-3">产品决策</h3>
                    <p class="text-gray-700">
                        产品经理评估不同LLM的安全性和逻辑一致性，指导供应商选择和产品规划。
                    </p>
                </div>
            </div>
        </div>
    </section>

    <!-- Getting Started Section -->
    <section class="py-16 px-6">
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            <h2 class="text-4xl font-bold text-center mb-12 serif-font">快速上手</h2>
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                            1
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                        <div>
                            <h3 class="text-lg font-bold mb-2">访问平台</h3>
                            <p class="text-gray-700">打开 lmarena.ai，点击"Start Battling"开始体验，无需注册即可使用。</p>
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                            <h3 class="text-lg font-bold mb-2">选择竞技场</h3>
                            <p class="text-gray-700">根据需求选择文本、图像或其他模态的竞技场，了解评估规则。</p>
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                        <div class="bg-purple-600 text-white rounded-full w-10 h-10 flex items-center justify-center font